OBJECTIVES: Healthcare payers frequently implement coverage policy (e.g., step therapy) to restrict access to high-cost, novel first-line treatments. To inform this practice, cost-effectiveness analysis (CEA) can be conducted to compare a new first-line treatment versus the existing one based on clinical trial results. However, this approach fails to acknowledge treatment effect heterogeneity, real-world treatment selection, and resources used to implement policies. We aimed to develop new policy-relevant metrics to better understand the value of expanding first-line treatment choices.

METHODS: We conceptualized an incremental cost-effectiveness ratio (ICER) metric to compare an expanded and a restricted choice set (CS) of first-line treatments (i.e., alternative policies). ICER-CS further relaxes three assumptions underlying in traditional CEA, including (1) no treatment selection driven by heterogeneous treatment effect, (2) no policy implementation cost, and (3) no future advance in subsequent line, by incorporating new parameters. We also developed an expected value of expanding choices (EVEC) metric to measure incremental net monetary benefits produced by expansion policy. Finally, we linked EVEC with the existing value of information concept to quantify decision uncertainties and prioritize future studies. These metrics were presented in a basic scenario of two treatment choices, followed by a more realistic scenario where some individuals are unwilling to undergo standard first-line treatments. We illustrated the framework using the case of abiraterone acetate (AA) for metastatic castration-sensitive prostate cancer.

RESULTS: The traditional societal-perspective ICER of first-line AA versus docetaxel was $201,000/QALY. After accounting for differential selection between age groups due to heterogeneity, the administrative burden of prior authorization, future subsequent-line treatments, and additional choice of androgen deprivation therapy alone, ICER-CS of allowing versus restricting AA was $147,000/QALY. The EVEC metric showed that the restriction policy would generate considerable welfare loss.

CONCLUSIONS: This framework can provide decision-makers with more policy-relevant tools to evaluate the potential value of expanding first-line treatment choices.